Browse > Article
http://dx.doi.org/10.7840/Kics.2014.39C.10.957

Fast Image Stitching For Video Stabilization Using Sift Feature Points  

Hossain, Mostafiz Mehebuba (Department Of Electrical Engineering And Computer Science, Seoul National University)
Lee, Hyuk-Jae (Department Of Electrical Engineering And Computer Science, Seoul National University)
Lee, Jaesung (Korea National University Of Transportation Department Of Electrical Engineering)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.39C, no.10, 2014 , pp. 957-966 More about this Journal
Abstract
Video Stabilization For Vehicular Applications Is An Important Method Of Removing Unwanted Shaky Motions From Unstable Videos. In This Paper, An Improved Video Stabilization Method With Image Stitching Has Been Proposed. Scale Invariant Feature Transform (Sift) Matching Is Used To Calculate The New Position Of The Points In Next Frame. Image Stitching Is Done In Every Frame To Get Stabilized Frames To Provide Stable Video As Well As A Better Understanding Of The Previous Frame'S Position And Show The Surrounding Objects Together. The Computational Complexity Of Sift (Scale-Invariant Feature Transform) Is Reduced By Reducing The Sift Descriptors Size And Resticting The Number Of Keypints To Be Extracted. Also, A Modified Matching Procedure Is Proposed To Improve The Accuracy Of The Stabilization.
Keywords
Video Stabilization; Sift; Image Stitching; Image Transformation; Ransac;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 S. Auberger and C. Miro, "Digital video stabilization architecture for low cost devices," Proc. 4th Int. Symp. Image and signal Process. Anal., pp. 474-479, Zagreb, Croatia, Sept. 2005.
2 H. C. Lee and D. M. Lee, "A study on the pattern matching algorithm of 3D coordinates for quality control in ship blocks," J. KICS, vol. 37, no. 10, pp. 933-939, Oct. 2012.   과학기술학회마을   DOI
3 S.-W. Jang, M. Pomplun, G.-Y. Kim, and H.-I. Choi, "Adaptive robust estimation of affine parameters from block motion vectors," Image and Vision Computing, vol. 23, no. 14, pp. 1250-1263, Dec. 2005.   DOI   ScienceOn
4 F. Vella, A. Castorina, M. Mancuso, and G. Messina, "Digital image stabilization by adaptive block motion vectors filtering," IEEE Trans. Consumer Electron., vol. 48, no. 3, pp. 796-801, Aug. 2002.   DOI   ScienceOn
5 S. Eriturk, "Image sequence stabilization based on kalman filtering of frame positions," IEEE Electron. Lett., vol. 37, no. 20, pp. 1217-1219, Sept. 2001.   DOI
6 L. M. Abdullah, N. Md Tahir, and M. Samad, "Video stabilization based on point feature matching technique," IEEE Control and System Graduate Research Colloquium, pp. 303-307, Shah Alam. Selangor, Malaysia, Jul. 2012.
7 M. Zhou and V. K. Asari, "A fast video stabilization system based on speed-up robust features," Advances in Visual Computing, pp. 428-435, Berlin, Germany, 2011.
8 G. Gankhuyag, E. G. Hong, G. Kim, Y. Kim and, Y. Choe, "A real-time video stitching algorithm in H.264/AVC compressed domain." J. KICS, vol. 39, no. 6, pp. 503-511, Jun. 2014.   과학기술학회마을   DOI
9 W.-R. Lee, K.-H. Kang, and J. Yoo, "Object-based conversion of 2D image to 3D," J. KICS, vol. 36, no. 9, pp. 555-563, Sept. 2011.   과학기술학회마을   DOI
10 D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Computer Vision, vol. 60, no. 2, pp. 91-110, Nov. 2004.   DOI   ScienceOn
11 V. F. da CamaraNeto, "An improved methodology for image feature matching," XXII Brazilian Symp. Computer Graphics and Image Processing, pp. 307-314, Rio de Janeiro, Brazil, Oct 2009.
12 R. Laganiere, OpenCV 2 Computer Vision Application Programming Cookbook, Packt Publishing, 2011.
13 Z. Yi, C. Zhiguo, and X. Yang "Multi-spectral remote image registration based on SIFT," IEEE Electron. Lett., vol. 44, no. 2. pp. 107-108, Jan. 2008.   DOI   ScienceOn
14 G. Bradski and A. Kaebler, Learning Opencv: Computer Vision with the Opencv Library, NY: O'Reilly, 2008.
15 M. A. Fishler and R. C. Bolles, "Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography," Commun. ACM, vol. 24, no. 6, pp. 381-395, Jun. 1981.   DOI   ScienceOn
16 Z. Qidan and L. Ke. "Image stitching using simplified SIFT," in Proc. IEEE Int. Conf. Inf. Automation, pp. 1134-1137, Harbin, China, Jan. 2010.
17 L. Ledwich and S. Williams, "Reduced SIFT features for image retrieval and indoor localisation," Australian Conf. Robotics and Automation, Canberra, Australia, Dec. 2004.
18 L. Lingjun and L.- Xiang, "LSIFT- an improved SIFT algorithm with a new matching methode," Int. Conf. Comput. Appl. Syst. Modelling, pp. V4-643-V4-646, Taiyuan, China, Oct. 2010.
19 Z. Ying and Li-Da-Hui. "Video image tracing based on improved sift feature matching algorithm," J. Multimedia, vol. 9, no. 1, pp. 130-137, Jan. 2014.
20 T. Chen, Video stabilization algorithm using a block-based parametric motion model, EE392J Project Report, Inf. Syst. Laboratory, Dept. of Electrical Engineering, Stanford University, United States America, 2000.
21 P. Du, Y. Zhou, Q. Xing, and X. Hu, "Improved SIFT matching algorithm for 3D reconstruction from endoscopic images," VRCAI: Virtual Reality Continuum and its Applications in Industry, pp. 561-564, New York, United States of America, 2011.